Fullstack Software Engineer - Business Solutions - Onsite or Remote (FR, UK, DE, NL)

Tbwa Chiat/Day Inc
Myddle
2 months ago
Applications closed

Related Jobs

View all jobs

Full Stack Developer

Full Stack Software Developer

Head of Development - Fintech SaaS. Full Remote

Head of Development - Fintech SaaS. Full Remote

Head of Development - Fintech SaaS. Full Remote

Senior Software/Data Engineering Lead- Global Investment Bank | London, UK

Fullstack Software Engineer - Business Solutions - Onsite or Remote (FR, UK, DE, NL)

Europe, Middle East, and Africa

At Dataiku, we're not just adapting to the AI revolution, we're leading it. Since our beginning in Paris in 2013, we've been pioneering the future of AI with a platform that makes data actionable and accessible. With over 1,000 teammates across 25 countries and backed by a renowned set of investors, we're the architects of Everyday AI, enabling data experts and domain experts to work together to build AI into their daily operations, from advanced analytics to Generative AI.

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators.

In Business Solutions, we are building apps that leverage Dataiku’s capabilities in data and AI, focused on key enterprise use cases that need their own, user-focused UIs and flows. In short: our work truly is part of “everyday AI”!

How you’ll make an impact

  • Build Innovative AI-Driven Applications:Design, develop, and deploy AI-powered applications that solve complex business problems, integrating Dataiku’s backend AI capabilities with user-centric, intuitive front-end interfaces.
  • Work with Data Scientists and Industry Specialists:Collaborate with solutions engineers, data scientists, and industry experts to develop the best solutions for customers.
  • Drive Continuous Improvement:Take responsibility for the end-to-end lifecycle of applications—from PoC to production.
  • Collaborate Across Teams:Work closely with core teams to ensure high-quality, reusable components.
  • Contribute to Team Growth:Help mentor new team members and contribute to onboarding processes.

What you’ll need to be successful

  • Full-Stack Development Experience: Experience in full-stack software engineering, with experience taking an app from PoC to production.
  • Front-End Skills: Proficiency in modern reactive front-end frameworks like Vue.js (preferred), React, or Angular.
  • Back-End Skills: Strong experience with backend development, especially with Python (FastAPI, Flask, etc.).
  • Experience with Data-Intensive Applications: Understand the challenges of working with large datasets.
  • Customer-Oriented Mindset: Strong focus on solving real-world problems for customers.
  • Curiosity: Excited to learn, adapt, and take on new challenges.
  • Tech Enthusiast: Passionate about AI and data-driven applications.

What does the hiring process look like?

  • 45 min call with a Technical Recruiter
  • Technical video interview with an Engineering Team Lead
  • Take home assignment or Live Coding session
  • 2 last interviews with VPs of Engineering

What are you waiting for!

At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku!

Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.